Zhang Fan, Xue Mengjuan, Jiang Xin, Yu Huiyuan, Qiu Yixuan, Yu Jiaming, Yang Fan, Bao Zhijun
Department of Geriatric Medicine, Huadong Hospital, Shanghai Medical College, Fudan University, No. 221 Yan'an West Road, Shanghai, 200040, People's Republic of China.
Shanghai Key Laboratory of Clinical Geriatric Medicine, Huadong Hospital, Shanghai Medical College, Fudan University, No. 221 Yan'an West Road, Shanghai, 200040, People's Republic of China.
Cancer Cell Int. 2021 Mar 17;21(1):174. doi: 10.1186/s12935-021-01871-6.
The incidence and mortality rates of hepatocellular carcinoma are among the highest of all cancers all over the world. However the survival rates are relatively low due to lack of effective treatments. Efforts to elucidate the mechanisms of HCC and to find novel prognostic markers and therapeutic targets are ongoing. Here we tried to identify prognostic genes of HCC through co-expression network analysis.
We conducted weighted gene co-expression network analysis with a microarray dataset GSE14520 of HCC from Gene Expression Omnibus database and identified a hub module associated with HCC prognosis. Function enrichment analysis of the hub module was performed. Clinical information was analyzed to select candidate hub genes. The expression profiles and survival analysis of the selected genes were performed using additional datasets (GSE45267 and TCGA-LIHC) and the hub gene was identified. GSEA and in vitro experiments were conducted to further verify the function of the hub gene.
Genes in the hub module were mostly involved in the metabolism pathway. Four genes (SLC27A5, SLC10A1, PCK2 and FMO4) from the module were identified as candidate hub genes according to correlation analysis with prognostic indicators. All these genes were significantly down-regulated in tumor tissues compared with non-tumor tissues in additional datasets. After survival analysis and network construction, SLC27A5 was selected as a prognostic marker. GSEA analysis and in vitro assays suggested that SLC27A5 downregulation promoted tumor cell migration via enhancing epithelial-mesenchymal transition.
SLC27A5 is a potential biomarker of HCC and SLC27A5 downregulation promoted HCC progression by enhancing EMT.
肝细胞癌的发病率和死亡率在全球所有癌症中位居前列。然而，由于缺乏有效的治疗方法，其生存率相对较低。目前正在努力阐明肝癌的发病机制，并寻找新的预后标志物和治疗靶点。在此，我们试图通过共表达网络分析来鉴定肝癌的预后基因。
我们使用来自基因表达综合数据库的肝癌微阵列数据集GSE14520进行加权基因共表达网络分析，并鉴定出一个与肝癌预后相关的枢纽模块。对该枢纽模块进行功能富集分析。分析临床信息以选择候选枢纽基因。使用其他数据集（GSE45267和TCGA-LIHC）对所选基因进行表达谱分析和生存分析，并鉴定出枢纽基因。进行基因集富集分析（GSEA）和体外实验以进一步验证枢纽基因的功能。
枢纽模块中的基因大多参与代谢途径。根据与预后指标的相关性分析，该模块中的四个基因（SLC27A5、SLC10A1、PCK2和FMO4）被鉴定为候选枢纽基因。在其他数据集中，与非肿瘤组织相比，所有这些基因在肿瘤组织中均显著下调。经过生存分析和网络构建，SLC27A5被选为预后标志物。GSEA分析和体外实验表明，SLC27A5的下调通过增强上皮-间质转化促进肿瘤细胞迁移。
SLC27A5是肝癌的潜在生物标志物，SLC27A5的下调通过增强上皮-间质转化促进肝癌进展。
